Getting Started with Regression in R

In person 

This course introduces you to regression analysis, a commonly used statistical tool for examining how one factor (e.g., Exam Scores) relates to one or several other factors (e.g., Hours studied, Course attendance, Prior Proficiency, etc.). It will develop your theoretical understanding and practical skills for running regression models in R. 

This course consists of two 2-hour sessions. 

The sessions integrate concept-focused discussions and practical R-based activities. By the end of the course, you will understand key regression concepts and be able to perform regression analysis in R. 

Key Concepts Covered: 

• Variables (Dependent vs. Independent)

• Linearity

• Residuals

• Coefficients (Intercepts vs. Slopes)

   

Key Practicals Include: 

• Model Fitting; 

• Checking Model Assumptions; 

• Visualising Fitted Models. 

While this course is suitable for beginners, a basic understanding of R and statistical analyses is recommended. Participants should ensure R and the necessary packages are installed prior to the course. 

Those who have registered to take part will receive an email with full details on how to get ready for the course.

This course will be taught by Fang Yang. 

After taking part in this event, you may decide that you need some further help in applying what you have learnt to your research. If so, you can book a Data Surgery meeting with one of our training fellows. 

More details about Data Surgeries. 

Those who have registered to take part will receive an email with full details on how to get ready for this course. 

If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event. 

Level  

This workshop requires the following pre-knowledge:   

• Familiarity with working with R  

• Familiarity with handling and wrangling data and installing packages 

• Familiarity with statistical analysis concepts, such as the correlation between two variables 

Learning Outcomes 

• Understand the concept of residuals, coefficients and the linear relationship between variables

• Understand how to perform model fitting and selection and interpret the model assumptions

• Know how to construct a regression analysis in R

Skills  

• Fitting and running regression models in R 

• Assessing and interpreting model assumptions 

• Visualising and interpreting regression results 

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Return to the Training Homepage to see other available events